Impact of odour emissions from livestock operation sites on the air quality of neighboring areas has raised public concerns. A practical means to solve this problem is to set adequate setback distance. Air dispersion modeling was proved to be a promising method in predicting proper odour setback distance. Although a lot of air dispersion models have been used to predict odour concentrations downwind agricultural odour sources, not so much information regarding the capability of these models in odour dispersion modeling simulation could be found because very limited field odour data are available to be applied to evaluate the modeling result. A main purpose of this project was evaluating AERMOD and CALPUFF air dispersion models for odour dispersion simulation using field odour data.<p>
Before evaluating and calibrating AERMOD and CALPUFF, sensitivity analysis of these two models to five major climatic parameters, i.e., mixing height, ambient temperature, stability class, wind speed, and wind direction, was conducted under both steady-state and variable meteorological conditions. It was found under steady-state weather condition, stability class and wind speed had great impact on the odour dispersion; while, ambient temperature and wind direction had limited impact on it; and mixing height had no impact on the odour dispersion at all. Under variable weather condition, maximum odour travel distance with odour concentrations of 1, 2, 5 and 10 OU/m3 were examined using annual hourly meteorological data of year 2003 of the simulated area and the simulation result showed odour traveled longer distance under the prevailing wind direction.<p>
Evaluation outcomes of these two models using field odour data from University of Minnesota and University of Alberta showed capability of these two models in odour dispersion simulation was close in terms of agreement of modeled and field measured odour occurrences. Using Minnesota odour plume data, the difference of overall agreement of all field odour measurements and model predictions was 3.6% applying conversion equation from University of Minnesota and 3.1% applying conversion equation from University of Alberta between two models. However, if field odour intensity 0 was not considered in Minnesota measured odour data, the difference of overall agreement of all field odour measurements and model predictions was 3.1% applying conversion equation from University of Minnesota and 1.6% applying conversion equation from University of Alberta between two models. Using Alberta odour plume data, the difference of overall agreement of all field odour measurements and model predictions was 0.7% applying conversion equation from University of Alberta and 1.2% applying conversion equation from University of Minnesota between two models. However, if field odour intensity 0 was not considered in Alberta measured odour data, the difference of overall agreement of all field odour measurements and model predictions was 0.4% applying conversion equation from University of Alberta and 0.7% applying conversion equation from University of Minnesota between two models. Application of scaling factors can improve agreement of modeled and measured odour intensities (including all field odour measurements and field odour measurements without intensity 0) when conversion equation from University of Minnesota was used.<p>
Both models were used in determining odour setback distance based on their close performance in odour dispersion simulation. Application of two models in predicting odour setback distance using warm season (from May to October) historical annul hourly meteorological data (from 1999 to 2002) for a swine farm in Saskatchewan showed some differences existed between models predicted and Prairie Provinces odour control guidelines recommended setbacks. Accurately measured field odour data and development of an air dispersion model for agricultural odour dispersion simulation purpose as well as acceptable odour criteria could be considered in the future studies.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:SSU.etd-09292009-171346 |
Date | 30 September 2009 |
Creators | Li, Yuguo |
Contributors | Guo, Huiqing, Noble, Scott D., Predicala, Bernardo Z., Chen, Li |
Publisher | University of Saskatchewan |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | http://library.usask.ca/theses/available/etd-09292009-171346/ |
Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Saskatchewan or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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